[T07] AI Engineer - Permanent

TALENTSIS PTE. LTD.; Singapore; On-site; SGD 150,000 - 190,000; Full time

Job summary

TALENTSIS PTE. LTD. is seeking an experienced AI/ML Lead to architect and deploy production-grade, geospatial ML solutions.

You will work with software engineers to integrate AI capabilities into end-to-end platforms and drive MLOps to ensure system reliability and performance. Responsibilities include leading model development, deploying ML services with API layers (Flask/FastAPI/Node.js) and Docker-based environments, and mentoring engineers across cross-functional teams.

Qualifications

• Degree in Computer Science, Electrical Engineering, or a related discipline.
• At least 5 years of experience developing and deploying production-grade ML solutions.
• Proficient in Python with ML frameworks such as PyTorch and scikit-learn and computer vision with OpenCV.
• Experience deploying ML services and API development using Flask, FastAPI, or Node.js; containerisation with Docker.
• Experience with LLMs, Retrieval-Augmented Generation (RAG), retrieval optimisation, and graph databases is advantageous.
• Self-motivated with strong ownership, stakeholder management, and communication skills.
• Ability to mentor engineers and collaborate across technical and business teams.

Responsibilities

• Provide technical leadership in designing, developing, and deploying production-grade AI and ML solutions for geospatial applications.
• Architect scalable ML systems and integrate AI capabilities into end-to-end platforms with software engineers.
• Drive model performance, reliability, and MLOps through deployment, monitoring, and optimisation.
• Collaborate with product, business development, and sales to translate requirements into technical solutions and plans.
• Mentor engineers and guide technical decision-making within the team.
• Support pre-sales and post-sales activities with technical expertise and consultation.

Skills

LLMs

RAG

Graph databases

Python

PyTorch

scikit-learn

OpenCV

Flask

FastAPI

Node.js

Docker

Education

Degree in Computer Science, Electrical Engineering, or a related discipline

Tools

Flask

FastAPI

Node.js

Docker

Job description

Responsibilities

• Provide technical leadership in the design, development, and deployment of production-grade AI and machine learning solutions, with a focus on geospatial applications.
• Design and architect scalable machine learning systems, working closely with software engineers to integrate AI capabilities into end-to-end platforms.
• Drive model performance, system reliability, and continuous improvement through MLOps best practices, including deployment, monitoring, and optimisation.
• Collaborate with product, business development, and sales teams to translate business requirements into clear technical solutions and delivery plans.
• Provide technical guidance and mentorship to engineers, supporting technical decision-making and capability development within the team.
• Support pre-sales and post-sales activities by providing technical expertise and consultation where required.

Requirements

• Degree in Computer Science, Electrical Engineering, or a related discipline.
• At least 5 years of relevant experience in developing and deploying production-grade machine learning solutions.
• Strong foundation in machine learning and deep learning, including model development, evaluation, and optimisation.
• Proficient in Python, with hands-on experience in machine learning frameworks such as PyTorch and scikit-learn, as well as computer vision libraries such as OpenCV.
• Experience in deploying and maintaining ML services, including API development using Flask, FastAPI, or Node.js, and containerisation using Docker.
• Experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), retrieval optimisation, and graph databases will be advantageous.
• Self-motivated and proactive, with strong ownership, stakeholder management, and communication skills.
• Ability to mentor team members and collaborate effectively across technical and business teams.
• (EA Reg No: 20C0312)